There are 4 repositories under ssvep topic.
Code to accompany our International Joint Conference on Neural Networks (IJCNN) paper entitled - Simulating Brain Signals: Creating Synthetic EEG Data via Neural-Based Generative Models for Improved SSVEP Classification
Classification toolbox for ERP and SSVEP based BCI data
The SSVEP Keyboard works with the icibici hardware. Once connected you should be able to look at keys and it will type them for you.
SSVEP-based BCI recording of 12 subjects operating an upper limb exoskeleton during a shared control task. The exoskeleton is either controlled with a touchless interface detecting hand poses or with BCI.
Code to accompany our International Conference on Pattern Recognition (ICPR) paper entitled - Leveraging Synthetic Subject Invariant EEG Signals for Zero Calibration BCI.
Using multi-task learning to capture signals simultaneously from the fovea efficiently and the neighboring targets in the peripheral vision generate a visual response map. A calibration-free user-independent solution, desirable for clinical diagnostics. A stepping stone for an objective assessment of glaucoma patients’ visual field.
A basic demonstration how to use Python, MNE, and PyTorch to analyze EEG signal.
EEG BCI Real-Time Applications: Contains real-time demonstrations of BCI applications
The source code of the OACCA introduced in our IEEE TBME paper (10.1109/TBME.2021.3133594)
Matlab code of our IEEE TASE paper "Wong, C. M., Wang, Z., Rosa, A. C., Chen, C. P., Jung, T. P., Hu, Y., & Wan, F. (2021). Transferring subject-specific knowledge across stimulus frequencies in SSVEP-based BCIs. IEEE Transactions on Automation Science and Engineering, 18(2), 552-563."
SSVEP Brain Computer Interface - Example code for real-time detection of SSVEP using the Canonical Correlation Analysis (CCA) code in real-time. Implemented using OpenViBE and Python
High School SSVEP-BCI Research Project to improve classification accuracy of captured EEG signals
C# program to superpose SSVEP and c-VEP flickers on top of other graphical interfaces
Code to accompany our International Conference on Robotics and Automation (ICRA) paper entitled - Using variable natural environment brain-computer interface stimuli for real-time humanoid robot navigation.
Data mining based approach to study the effect of caffeinated coffee on SSVEP brain signals. https://doi.org/10.1016/j.compbiomed.2019.103526
Code to accompany our 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) paper entitled - On the classification of SSVEP-based dry-EEG signals via convolutional neural networks.
Simulations of stimulus-stimulus transfer based on time-frequency-joint representation in SSVEP-based BCIs. The proposed stimulus-stimulus transfer method has been published in IEEE TBME (DOI: 10.1109/TBME.2022.3198639)
uniBrain Speller: A one-stop, user-friendly, open-source brain-computer interface speller software developed by Prof. Gao Xiaorong's team at Tsinghua University, China, designed for various users including patients, researchers, and practitioners.
Library for visual flickering stimuli to evoke SSVEP response
Gaze data -based epoch selection algorithm for eye tracker assisted visual evoked potential paradigm
This repository contains code for analyzing Steady-State Visually Evoked Potential (SSVEP) signals recorded from EEG data. The goal of this analysis is to determine the stimulation frequency from the EEG signals recorded in each test. Two methods are employed: Frequency Content Plotting and Canonical Correlation Analysis (CCA).
Deep Learning toolbox for EEG based Brain-Computer Interface signals decoding and benchmarking
Data and code for the metrological characterization of a low-cost wearable brain-computer interface
Direct ITR optimisation for SSVEP-based BCI
Unity gaming project for the BR41N.io Hackathon at g.tec's Spring School 2023. Unicorn Unity Interface Hybrid Black and real-time EEG data.
CSS and WebGL were adopted to implement four cross-platform Steady State Visually Evoked Potential (SSVEP) stimuli-generator libraries, whose stimuli are produced via constant-period and square wave approximation techniques, for use in a Brain-Computer Interface (BCI) context. These libraries are configured to run as spellers, yet can easily be altered to cater for a wide range of use cases.
transfer learning canonical correlation analysis for SSVEP-BCIs
Information Bottleneck as Optimisation Method for SSVEP-Based BCI
Neuroexon presents a hybrid-BCI system that utilizes motor imagery (MI) and steady-state visual-evoked potential (SSVEP) to control a one degree of freedom arm exoskeleton which provides the user with haptic feedback.
Workshop on standardized Brain-Computer Interface Framework